Mouse analysis

Colon

plotUnsupervisedClass(uObjC, cObjSngC)

plotUnsupervisedMarkers(uObjC, cObjSngC, c("Lgr5", "Muc2", "Ptprc", "Chga", "Slc40a1"))

plotUnsupervisedMarkers(uObjC, cObjSngC, c("Mki67"))

Small Intestine

plotUnsupervisedClass(uObjSi, cObjSngSi)

plotUnsupervisedMarkers(
  uObjSi, cObjSngSi, 
  c("Lgr5", "Muc2", "Ptprc", "Chga", "Alpi", "Lyz1", "Dclk1"), 
  pal = RColorBrewer::brewer.pal(7, "Set2")
)

plotUnsupervisedMarkers(uObjSi, cObjSngSi, c("Mki67"))

All

plotUnsupervisedClass(uObj, cObjSng)

plotUnsupervisedMarkers(
  uObj, cObjSng,
  c("Lgr5", "Muc2", "Ptprc", "Chga", "Alpi", "Lyz1", "Dclk1", "Slc40a1"), 
  pal = RColorBrewer::brewer.pal(8, "Set1")
)

plotUnsupervisedClass(uObj, cObjSng) %>%
  plotData() %>%
  full_join(countsMgfpMeta, by = c("Sample" = "sample")) %>%
  filter(!is.na(`t-SNE dim 1`)) %>%
  mutate(tissue = if_else(str_detect(Sample, "SRR"), "SI", tissue)) %>%
  ggplot() +
  geom_point(aes(`t-SNE dim 1`, `t-SNE dim 2`, colour = tissue)) +
  ggthemes::theme_few()

plotUnsupervisedClass(uObj, cObjSng) %>%
  plotData() %>%
  full_join(countsMgfpMeta, by = c("Sample" = "sample")) %>%
  filter(!is.na(`t-SNE dim 1`)) %>%
  mutate(tissue = if_else(str_detect(Sample, "SRR"), "SI", tissue)) %>%
  mutate(plate = if_else(is.na(plate), "Regev", plate)) %>%
  ggplot() +
  geom_point(aes(`t-SNE dim 1`, `t-SNE dim 2`, colour = plate), alpha = 0.75) +
  ggthemes::theme_few() +
  scale_colour_manual(values = col40())

plotUnsupervisedClass(uObj, cObjSng) %>%
  plotData() %>%
  full_join(countsMgfpMeta, by = c("Sample" = "sample")) %>%
  filter(!is.na(`t-SNE dim 1`)) %>%
  mutate(total.counts = map_dbl(Sample, function(s) {
    sum(getData(cObjSng, "counts")[, s])
  })) %>%
  mutate(total.counts.bin = ntile(total.counts, 10)) %>%
  group_by(total.counts.bin) %>%
  mutate(total.counts.mean = mean(total.counts)) %>%
  ggplot() +
  geom_point(aes(`t-SNE dim 1`, `t-SNE dim 2`, colour = total.counts.mean)) +
  ggthemes::theme_few() +
  viridis::scale_colour_viridis(option = "E") +
  guides(colour = guide_colorbar(title = "Binned total counts")) +
  labs(caption = paste0(
    "Total counts were calculated for each sample. The total counts were then ",
    "evenly divided into 10 bins for the whole dataset and the mean\n ",
    "total counts calculated for each bin. This mean was then portrayed as the ",
    "point colour in the figure."
  )) +
  theme(
    plot.caption = element_text(hjust = 0)
  )

plotUnsupervisedClass(uObj, cObjSng) %>%
  plotData() %>%
  full_join(countsMgfpMeta, by = c("Sample" = "sample")) %>%
  filter(!is.na(`t-SNE dim 1`)) %>%
  mutate(total.counts = map_dbl(Sample, function(s) {
    sum(getData(cObjSng, "counts")[, s])
  })) %>%
  mutate(total.counts.bin = ntile(total.counts, 10)) %>%
  group_by(total.counts.bin) %>%
  mutate(total.counts.mean = mean(total.counts)) %>%
  mutate(Regev = if_else(str_detect(Sample, "SRR"), TRUE, FALSE)) %>%
  ggplot() + 
  geom_boxplot(aes(Regev, total.counts)) +
  theme_bw()

plotUnsupervisedMarkers(uObj, cObjSng, "Lyz1") %>%
  plotData() %>%
  full_join(countsMgfpMeta, by = c("Sample" = "sample")) %>%
  filter(!is.na(`t-SNE dim 1`)) %>%
  mutate(regev = if_else(str_detect(Sample, "SRR"), TRUE, FALSE)) %>%
  filter(Classification == "S1") %>%
  ggplot() +
  geom_point(
    aes(`t-SNE dim 1`, `t-SNE dim 2`, shape = regev, colour = Lyz1), 
    size = 3
  ) +
  viridis::scale_colour_viridis(option = "E") + 
  theme_few()

plotUnsupervisedMarkers(uObj, cObjSng, "Defa24") %>%
  plotData() %>%
  full_join(countsMgfpMeta, by = c("Sample" = "sample")) %>%
  filter(!is.na(`t-SNE dim 1`)) %>%
  mutate(regev = if_else(str_detect(Sample, "SRR"), TRUE, FALSE)) %>%
  filter(Classification == "S1") %>%
  ggplot() +
  geom_point(
    aes(`t-SNE dim 1`, `t-SNE dim 2`, shape = regev, colour = Defa24), 
    size = 3
  ) +
  viridis::scale_colour_viridis(option = "E") + 
  theme_few()

plotUnsupervisedMarkers(uObj, cObjSng, "Defa17") %>%
  plotData() %>%
  full_join(countsMgfpMeta, by = c("Sample" = "sample")) %>%
  filter(!is.na(`t-SNE dim 1`)) %>%
  mutate(regev = if_else(str_detect(Sample, "SRR"), TRUE, FALSE)) %>%
  filter(Classification == "S1") %>%
  ggplot() +
  geom_point(
    aes(`t-SNE dim 1`, `t-SNE dim 2`, shape = regev, colour = Defa17), 
    size = 3
  ) +
  viridis::scale_colour_viridis(option = "E") + 
  theme_few()

d <- plotUnsupervisedClass(uObj, cObjSng) %>%
  plotData() %>%
  inner_join(countsMgfpMeta, by = c("Sample" = "sample")) %>%
  select(Sample, Classification, plate:column, mouseID) %>%
  filter(Classification == "S1") %>%
  mutate(total.counts = map_dbl(Sample, function(s) {
    sum(getData(cObjSng, "counts")[, s])
  })) %>%
  mutate(Lyz1.cpm = map_dbl(Sample, function(s) {
    getData(cObjSng, "counts")["Lyz1", s]
  })) %>%
  mutate(Defa24.cpm = map_dbl(Sample, function(s) {
    getData(cObjSng, "counts")["Defa24", s]
  })) %>%
  mutate(Defa17.cpm = map_dbl(Sample, function(s) {
    getData(cObjSng, "counts")["Defa17", s]
  }))

as.data.frame(d)